Financial Inclusion & Risk: Alternative Credit Scoring
Approve more good borrowers - responsibly.
Unlock credit for new-to-credit and thin-file customers with explainable, alternative-data scoring. FIA Global’s solution blends cash-flow insights, behavioral signals, and policy overlays to raise approvals while protecting portfolio quality.
Customer Benefits
Scores Thin-file Applicants
Uses consented alternative data (cash-flow, device/usage, utilities, behavior)
Decision Explainations
Provides reason codes; supports policy overlays and manual review queues
System Monitoring
Monitors model drift & portfolio health with challenger testing and fairness checks
Core capabilities
Data & Consent Orchestration
Bank statements, device/usage, utility, behavioral; consent ledger
Cash-Flow & Stability Features
Inflows/outflows, income proxies, variance, recency, irregularity
Explainable
Scorecards
Reason codes, adverse-action notices, human-in-the-loop controls
Decision
Engine
Policy rules, risk tiers, pricing bands, referral/exception queues
Monitoring
& Fairness
Drift, back-testing, bias checks, champion–challenger models
Deployment
Options
Low-latency API or on-prem container; full logs for audit & governance
Built for regulated financial services
Designed for banks, NBFCs, MFIs, and fintech lenders operating in regulated environments—privacy, consent, security, and auditability baked in from day one.
Ecosystem & Interoperability
Works with: bureaus, bank statement analyzers, identity & fraud services
Integrates to: LOS/LMS, core banking, CRM, data lakes/warehouses
Operate anywhere: cloud, hybrid, or fully on-prem with your data-residency rules
Risk, Compliance & Governance
Regulatory posture: consented data, retention controls, reproducible evidence
Controls: maker–checker, role-based access, model versioning & lineage
Evidence: downloadable logs, score explanations, and audit trails
Outcomes and Stakeholders
Time to Value
Pilot in 8–12 weeks with champion–challenger setup and clear success criteria.
Outcome Snapshot
Approval uplift 10–25% at target risk bands
Turnaround time reduced from days to hours with automated decisioning
(Outcomes indicative; actuals depend on data quality, policy, and portfolio mix.)
Typical Trackable KPIs
Approval rate uplift vs baseline (by product/segment/risk band)
Early-risk indicators: first-pay default, 30/60 DPD, roll-rates, cure rates
Decisioning TAT (auto-approve/auto-decline/manual review)
Model drift & stability metrics (PSI/CSI), fairness & bias checks
Pricing/ROI: expected loss, risk-adjusted margin, lifetime value
Who Uses It
Credit & Risk: policy design, cut-offs, overrides, portfolio monitoring
Product & Growth: new segments, pricing bands, offer strategies
Collections: early-warning flags, pre-emptive outreach cohorts
Compliance & Audit: explainability evidence, adverse-action notices, logs
Analytics & IT: model lifecycle, data governance, integrations
FAQs
We've got the answers you're looking for.
Is the model explainable to regulators and customers?
Yes—reason codes and adverse-action language are generated for every decision.
Can we add our own rules and pricing tiers?
Absolutely—the decision engine supports policy overlays and custom tiers.
Do we have to send data to the cloud?
No—run the scorer fully on-prem or in your private cloud if required.
Will it replace our bureau-based score?
It can complement or augment bureau scores; you control weightage and cut-offs.
Ready to approve more good borrowers—responsibly?
Explore Scoring Models → We’ll review your data, define risk bands, and stand up a champion–challenger pilot.
